Introduction to availability modelling in ELMAS

Arto Niemi

Introduction

• Arto Niemi, PhD student at Tampere University of Technology in a group of Reliability Engineering• Work before in projects involving • Aircraft reliability and prognostics studies and

method development• Power plant operation cost and availability analysis

for warranty cost calculation • Telecommunication maintenance strategy

optimization, data driven diagnostics (SOM) and general data analytics

RAMS for FCC

• The goal of the project is develop methods and tool for availability analysis to be used in FCC study• However, to develop the methods and test their

applicability we work with the data from LHC and the injector chain• The main task is to develop a high level fault

tree model for “generic” accelerator to be used to study current accelerators and future ones.

The Model

• The model is made with ELMAS software from Finnish company Ramentor • The model has three levels: • L1: Runs and long shutdowns• L2 Annual level: proton physics, technical stops, etc.• L3 Proton physics operations: Stable beams, turn around… www.ramentor.com

Maintenance Operation Maintenance Operation Maintenance Operation

Time (years)

Level 1

Idle Cycle Failed Idle Cycle Failed

Prepare Deliver Recycle Isolate Notify Logistics Restore

Level 2

Level 3

Level 2 Model Schematic

• The year starts with commissioning followed by proton physics• The proton physics is interrupted by technical stops and machine

development

Level 3 Model

• The phases (green) activate different parts of the fault tree (blue)• Under these nodes will be

the nodes for the failure modes Magnets, RF, Vacuum…• If the failure rate is phase

independent it’s just under the phase independent failures

The Injector Chain

• The injection is special as failure can occur either in the accelerator (LHC) or in it’s injector chain• From the LHC the injector

chain goes all the way back to Linac2 and contains all the transfer lines

Probabilistic availability analysis

• In the model the failures cause unavailability as any risk the probability and consequence are needed.• The probability of failure is given by failure rate,

which can be calculated from data or estimated by experts. • The rate can time dependent different rate at different

operational phases or “age” dependent• After technical stop failure rate seems to increase. we plan

to repeat 2011 TS analysis* with 2015 data

• The consequence is not only the repair time. • If the failure occurs during the stable beams or during a

turnaround the amount of lost production is different. • Some failures need pre-cycle

𝑅𝑖𝑠𝑘=𝑃𝑟𝑜𝑏∗𝐶𝑜𝑛𝑠𝑒𝑞𝑢𝑒𝑛𝑐𝑒𝑠

A schematic from A. Apollonio’s PhD thesis. *Matteo Solfaroli Camillocci, Evian 2011

Conclusions• The time dependency of the failure rate and

consequences leads very quickly very complex cause consequence logics. So, analytical solution is not practical and Monte-Carlo simulation is needed.• We work in collaboration with IT to have data

easily available• Modelling of the LHC is needed for verification

that model produces accurate results.• Once that is done the model can be used for

testing “what if” scenarios and more detail can be added to interesting systems.

A figure from A. Apollonio’s PhD thesis.

What if injection and turnaround lasts 10 hours for FCC?

TS analysis resultsBy M. Solfaroli Camillocci, Evian 2011

Extra slides

M.Solfaroli - Technical Stops 11Evian - 12/12/11

WHERE WERE WE?

Slot of 1.38 TeV operation Last 3.5 TeV physics fill (1645):• 200 b (24 bpinj) - (ready for 296 b)• ~1.22E11 p per bunch• Peak lumi: 2.5E32 cm-2 s-1

TS#128 – 31 March – 4 days + 1 recovery day

60%

30%10%

3243 keys given

GOAL of the weekRecovery from TS and start

preparation for high intensity

M.Solfaroli - Technical Stops 12

Sat 2nd ~2pm

Recovery

Evian - 12/12/11

TS#1 - Recovery

tThu 31st 6.25pm

CRYO

Fri 1st 10.29am

Fri 1st 9.59pm

Beam comm

Start of HWC

Global CRYO start First

pilot

Inj region aperture measurements for

higher intensity

Activity Duration [h]Tunnel activities (TS) 84

Recovery 31

Beam commissioning 12

TOT 127

MKB.B2

Sat 2nd 01.23am

Dump @450GeV

66%

10%24%

TOTAL NOT related HW SWTIME lost 14.5 h 48% 62% 38%

Mon 28th

7am

TS

M.Solfaroli - Technical Stops 13Evian - 12/12/11

Keys Maintenance Improving Problem fixing

TS#1 3243 60% 30% 10%

TS#2 2831 60% 24% 16%

TS#3 3062 65% 26% 9%

TS#4 3645 69% 24% 7%

TS#5 3404 70% 24% 6%

Tunnel activities vs TSs

Some numbers…

TS Analysis Results From 2011

M.Solfaroli - Technical Stops 14Evian - 12/12/11

Time lost [h] NOT related HW SW

TS#1 14.5 48% 62% 38%

TS#2 15.5 94% 90% 10%

TS#3 19.5 46% 85% 15%

TS#4 6.5 15% 8% 92%

TS#5 4 50% 62% 38%

Pretty low statistics to have meaningful conclusions......in general HW issues require more time to be fixed

…more…

M.Solfaroli - Technical Stops 15Evian - 12/12/11

…and more!Recovery + Beam

commissioningTOT TS time

(x-1)*24 + 12 + 24Recovery coefficient

(theoretical)Recovery

coefficient (real)

TS#1 43 h 108 h 0.22 0.4

TS#2 40 h(67 h including cryo stop) 108 h 0.22 0.37

TS#3 44 h(130 h considering the power cut) 132 h 0.18 0.33

TS#4 18 h 132 h 0.18 0.13

TS#5 13 h 132 h 0.18 0.09

X = number of days allocated Allocated time for recovery = 24 h

Recovery time vs TSs Recovery coefficient

M.Solfaroli - Technical Stops 16Evian - 12/12/11

Conclusions Need to improve fault details recording

Most of activities is maintenance, can it be reduced?

No systematic source of trouble over the 5 TSs !!

It seems clear that we are improving in recovery… (“After TS, an increment in faults was observed. Effect

is decreasing along the run” Walter @Chamonix 2011) Need to apply a control for SW changes (through a

meeting to coordinate and create a list?) which could: Improve changes, by coordinating them Increase operational efficiency, by making easier

the identification of the source of problems Reduce impact of changes on other systems

4 TSs foreseen for 2012...can we push forward some maintenance and have 3 TSs of 5 days?

2012